Paper
17 September 2013 An adaptive total variation image reconstruction method for speckles through disordered media
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Abstract
Multiple scattering of light in highly disordered medium can break the diffraction limit of conventional optical system combined with image reconstruction method. Once the transmission matrix of the imaging system is obtained, the target image can be reconstructed from its speckle pattern by image reconstruction algorithm. Nevertheless, the restored image attained by common image reconstruction algorithms such as Tikhonov regularization has a relatively low signal-tonoise ratio (SNR) due to the experimental noise and reconstruction noise, greatly reducing the quality of the result image. In this paper, the speckle pattern of the test image is simulated by the combination of light propagation theories and statistical optics theories. Subsequently, an adaptive total variation (ATV) algorithm—the TV minimization by augmented Lagrangian and alternating direction algorithms (TVAL3), which is based on augmented Lagrangian and alternating direction algorithm, is utilized to reconstruct the target image. Numerical simulation experimental results show that, the TVAL3 algorithm can effectively suppress the noise of the restored image and preserve more image details, thus greatly boosts the SNR of the restored image. It also indicates that, compared with the image directly formed by ‘clean’ system, the reconstructed results can overcoming the diffraction limit of the ‘clean’ system, therefore being conductive to the observation of cells and protein molecules in biological tissues and other structures in micro/nano scale.
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Changmei Gong, Xiaopeng Shao, and Tengfei Wu "An adaptive total variation image reconstruction method for speckles through disordered media", Proc. SPIE 8877, Unconventional Imaging and Wavefront Sensing 2013, 88770C (17 September 2013); https://doi.org/10.1117/12.2023573
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KEYWORDS
Image restoration

Signal to noise ratio

Reconstruction algorithms

Speckle pattern

Detection and tracking algorithms

Imaging systems

Eye

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